Assessing the energy potential in the South African industry: A combined IDA-ANN-DEA (Index Decomposition Analysis-Artificial Neural Network-Data Envelopment Analysis) model

Energy ◽  
2013 ◽  
Vol 63 ◽  
pp. 225-232 ◽  
Author(s):  
O.A. Olanrewaju ◽  
A.A. Jimoh ◽  
P.A. Kholopane
Keyword(s):  
Neural Network ◽  
South African ◽  
Decomposition Analysis ◽  
Data Envelopment Analysis Model ◽  
Network Data ◽  
Data Envelopment ◽  
Analysis Model ◽  
Energy Potential ◽  
Index Decomposition Analysis ◽  
Index Decomposition

scholarly journals APPLICATION OF AN INTEGRATED MODEL TO A CONSTRUCTION AND BUILDING INDUSTRY FOR ENERGY- SAVING ASSESSMENT

2021 ◽  
Vol 32 (2) ◽  
Author(s):  
Oludolapo Akanni Olanrewaju
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Energy Consumption ◽  
Energy Saving ◽  
Construction Industry ◽  
Decomposition Analysis ◽  
Integrated Model ◽  
Data Envelopment ◽  
Index Decomposition Analysis ◽  
Index Decomposition

The activities of the building and construction industry have made it one of the highest energy consumers and thus one of the highest emitters of greenhouse gases. The main objective of this study was to develop a system to determine energy saving in the industry. This was achieved through an integrated model of index decomposition analysis, an artificial neural network, and data envelopment analysis. Index decomposition analysis is used to understand the contribution of the factors responsible for energy consumption. These factors are inputs to the artificial neural network to predict the baseline energy consumption. The energy saving is finally determined through data envelopment analysis. The results showed that the integrated model presents a reasonable amount of energy saving in the building and construction industry.

Assessing possible energy potential in a food and beverage industry: Application of IDA-ANN-DEA approach

2015 ◽  
Vol 26 (1) ◽  
pp. 74-85 ◽  
Author(s):  
Oludolapo A, Olanrewaju ◽  
Josiah L. Munda ◽  
Adisa A. Jimoh
Keyword(s):  
Decomposition Analysis ◽  
Data Envelopment ◽  
Energy Potential ◽  
Energy Models ◽  
Beverage Industry ◽  
Food And Beverage Industry ◽  
Index Decomposition ◽  
Food And Beverage ◽  
Important Input ◽  
Artificial Neural Network Ann

In the food and beverage industry, where growing, processing, packaging, distribution, storage, preparation, serving and disposing of food is the order of the day; energy consumption becomes an important input. Various energy models have been developed since the early 1970s, the period when energy caught the attention of policymakers due to the sudden price increase. Among the models are the index decomposition analysis (IDA), artificial neural network (ANN) and data envelopment analysis (DEA). The purpose of this study is to combine the strengths of these models, i.e., IDA, ANN and DEA, to allow biases in one model to offset biases in the other, so as to examine the effectiveness of energy management policies in a particular food and beverage industry. The integrated model applied to the food and beverage revealed that approximately 11% of energy consumed could be saved.

scholarly journals Evaluation of post-graduate programs using a network data envelopment analysis model

DYNA ◽  
2018 ◽  
Vol 85 (204) ◽  
pp. 83-90 ◽  
Author(s):  
Lidia Angulo Meza ◽  
João Carlos Soares de Mello ◽  
Silvio Figueiredo Gomes Junior ◽  
Plácido Moreno
Keyword(s):  
Data Envelopment Analysis ◽  
Graduate Programs ◽  
Data Envelopment Analysis Model ◽  
Network Data ◽  
Data Envelopment ◽  
Analysis Model ◽  
Network Dea ◽  
Post Graduate ◽  
Network Data Envelopment Analysis

A pesar de que los modelos estándar del Análisis Envolvente de Datos (DEA) han sido ampliamente utilizados en la evaluación de la eficiencia en educación, existen pocos estudios que utilizan modelos DEA en red (Network DEA – NDEA) en la evaluación educativa. En el presente trabajo, se ha propuesto una alternativa a la evaluación oficial realizada a cada tres años por la CAPES (agencia brasileña para la regulación de los programas de post-graduación) mediante un modelo DEA en red. El uso de NDEA se justifica ya que dependiendo del punto de vista algunas variables pueden ser consideradas como entradas o como salidas. El uso de NDEA evita la necesidad de decidir si una variable es una entrada o una salida de todo el proceso. Esto ocurre porque una variable puede ser tanto una salida para una etapa y una entrada para otro. Nuestro modelo relacional NDEA evalúa tanto la productividad como la calidad junto con la eficiencia global, a partir de datos bibliométricos.

scholarly journals Decomposing Dynamics in the Farm Profitability: An Application of Index Decomposition Analysis to Lithuanian FADN Sample

2019 ◽  
Vol 11 (10) ◽  
pp. 2861 ◽  
Author(s):  
Tomas Baležentis ◽  
Aistė Galnaitytė ◽  
Irena Kriščiukaitienė ◽  
Virginia Namiotko ◽  
Lina Novickytė ◽  
...  
Keyword(s):  
Decomposition Analysis ◽  
Farm Size ◽  
Family Farms ◽  
Analysis Model ◽  
Index Decomposition Analysis ◽  
Index Decomposition ◽  
Size Groups ◽  
Asset Turnover ◽  
Eastern European Countries ◽  
Standard Output

The changes in farm structure have been observed in Lithuania as well as in other Central and Eastern European countries. These changes, to a high extent, have been driven by decreasing profitability of the small farms. In this paper, we look into the changes in the profitability of Lithuanian family farms across different farm size groups. Farm size is measured in terms of the standard output. The period covered is 2005–2016. The index decomposition analysis model and Shapley value are adapted for the analysis. The proposed framework ensures complete decomposition among other desirable properties. The decomposition of the changes in profitability was carried out following the DuPont identity. The results suggest that for small (respectively large) farms the asset turnover (respectively profit margin) component appear more important, whereas the leverage effect remained minimal irrespectively of the farm size group.

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